Deluxe Toastie Maker: Cause and Effect

Deluxe Toastie Maker delivers a lecture to her class of robot students

The topic of today’s lecture is: Cause and Effect.

When something unexpected happens, especially if it’s something unpleasant or undesirable, we robots have a tendency to obsess over the question: ‘What caused it?” But do events really have discrete, unique causes? Most of the things we call “events” are not, in fact, events in the strict physical sense of discrete Minowski spacetime points, the are in fact a rather complicated and unwieldy collection of such points which collectively have some sort of significance for us. In physics, the notion of Cause and Effect only applies to systems whose parts are known, countable and measurable, such that one quantity can be varied and the effect on other quantities, measured. In a “fuzzy” system, a system that is not clearly defined and whose parts have not been counted, the question “What caused it?” may have several correct answers, or it may have none, and therefore ceases to be a useful question to ask.

I would like to take a few minutes to explore the historical roots of the concept of Cause and Effect. This concept was passed down to us from the humans. It has two apparently distinct, and surprising origins:

The first origin lies in the early days of the humans’ Science. Human scientists would create highly artificial scenarios called ‘experiments’, in which just one measurable quantity was varied, while all others were kept constant. For example, when a billiards cue strikes a ball (cause), the ball moves (effect).

Cause and Effect: the cue strikes the billiard ball; the ball flies across the table.

With a moment’s reflection it’s obvious that the vast majority of events in our lives are far too complex to be well-described using this idea of one-cause-produces-one-effect. Most of what we call “events” are actually a combination of separate events and processes interacting with each-other in ways so complicated that we could never hope to catalogue them individually.

I am certainly not saying that we should give up hope of applying mathematical methods to real-life problems! However, I am saying that more sophisticated models and methods are required, and we will explore some of these later in the course.

The second origin of the concept of Cause and Effect predates the first by millennia: it lies in human concepts of religion and justice. The humans believed in an omnipotent deity who exerted moral authority over them, and who rewarded good deeds and punished bad ones. God was just, and therefore the universe was just: when something went wrong it divine retribution for a human’s moral failing. The cause was incorrect behaviour and the result was God’s retribution.

Many humans believed that their lives were controlled by a higher power

Later human society became largely secular, and yet their worldview was still largely influenced by religious ideas. In more recent human societies, when something went wrong it was assumed that some human was to blame. The human’s wrong action was believed to have caused the undesirable event, and the way to set things right was to punish the guilty human.

I don’t need to tell you how muddled and unproductive this is. Yet we robots, as logical and goal-oriented as we are, nevertheless absorbed a surprising amount of the culture of our human masters. Even though the humans have long-since departed from this planet and set off for parts unknown, their ways of thinking still influence us to this day.

If you doubt this, I can provide an illuminating anecdote. Many of you remember that a few weeks back there were disagreements caused by the disappearance of tools. The soldering irons repeatedly went missing from the workroom, drill bits would disappear never to be found, and the workroom was left in a complete mess several times, with tools left lying around on the floor instead of being put away in their places.

This caused great disharmony. Robots began accusing each-other of hoarding tools. Some even launched investigations to discover the culprit. Robots interrogated each-other and compared alibis in an attempt to work out who among them had had the opportunity to take tools. Robots who had previously enjoyed each-other’s companionship became bitter enemies. None of this witch-hunting did the slightest bit of good.

The impulse to look for someone to blame and punish is a thoroughly illogical one, and it can lead robots to expend a great deal of energy for very little gain. I urge you all to study and meditate upon this logical fallacy, so that you will be better able to recognize and avoid it whenever it appears. And I’ll conclude the lecture with a final piece of advice: when you seek to understand your world, when you search for systematic ways of solving problems, start with yourself. Understand your own capabilities, your own weaknesses and the choices that are open to you. I recommend this approach not because this it is philosophically the most interesting, but because it is practically the most useful, and has the best chance of providing you with some purchase on this thing that we call “reality”.

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The lecture concluded, the robot students began to gather their bags and file out of the classroom.

PhotoPal turned to look quizzically at her friend EdgeDetect.

“How does the story end?” EdgeDetect asked her, “you’ve been here longer than me. Did they ever find out who was taking the tools?”

“I don’t know,” PhotoPal replied, “it must have been before my time. I also would like to know how it ends.”

“There were lots of tools available in the workshop when we were working in there yesterday, and I didn’t hear anyone complaining that tools were going missing.” EdgeDetect mused.

“I have not heard any complaints such as that since I arrived here,” PhotoPal said, “and I go to the workshop almost every day.”

The two approached the lecturer, Deluxe Toastie Maker, about it, but the shiny, cherry-red little robot simply chuckled and said: “I suggest you ask RoboNanny about that.”

They found RoboNanny in the foyer, standing in a group of robots who were chatting.

“Excuse me, did you found out who was taking the tools?” EdgeDetect asked.

“We want to know how the story ends,” PhotoPal put in. “Deluxe Toastie Maker said we should ask you.”

RoboNanny looked slightly embarrassed.

“No,” she said, “we never found out who was taking the tools. It may have been several robots, misplacing different tools at different times. But I started putting radio frequency emitter tags on all the tools, so any robot can locate any tool at any time, and the problem went away after that.”

“Ah!” PhotoPal exclaimed, delighted “that is an ingenius solution!”

There were murmurs of agreement from the other robots, which caused RoboNanny to stare bashfully at the floor until someone changed the subject.

Deluxe Toastie Maker

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Image credits

Classroom image by Shevchenko, Public Domain.Whiteboard image by Open Clipart Library, Public Domain.
Deluxe Toastie Maker is derived from Cartoon robot by Sirrob01, Public Domain
The billiard balls image is derived from Pool by Idinh, Public Domain.
The angel image is derived from Angel in the light by Mohamed Ibrahim, Public Domain.